ArticlePharmacology research & perspectives2017
Clinician agreement and influence of medication-related characteristics on assessment of polypharmacy.
Article in Pharmacology research & perspectives, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.
- Identification of behaviour change techniques in deprescribing interventions: a systematic review and meta-analysis.British journal of clinical pharmacology · 2018Pooled it
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- Anticholinergic and sedative medications use among community dwelling older adults: risk for polypharmacy and poor physical function.BMC geriatrics · 2025Article
- The evaluation of relationship between polypharmacy and anticholinergic burden scales.Northern clinics of Istanbul · 2021Article
- Clinician agreement and influence of medication-related characteristics on assessment of polypharmacy.Pharmacology research & perspectives · 2017Article
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
It is not known how clinicians assess polypharmacy or the medication-related characteristics that influence their assessment. The aim of this study was to examine the level of agreement between clinicians when assessing polypharmacy and to identify medication-related characteristics that influence their assessment. Twenty cases of patients with varying levels of comorbidity and polypharmacy were used to examine clinician assessment of polypharmacy. Medicine-related factors within the cases included Beers and STOPP Criteria medicines, falls-risk medicines, drug burden index (DBI) medicines, medicines causing postural hypotension, and pharmacokinetic drug-drug interactions. Clinicians were asked to rate cases on the degree of polypharmacy, likelihood of harm, and potential for the medication list to be simplified. Inter-rater reliability analysis, correlations, and multivariate logistic regression analyses were conducted to identify medicine factors associated with clinicians' assessment. Eighteen expert clinicians were recruited (69.2% response rate). Strong agreement was observed in clinicians' assessment of polypharmacy (intraclass correlation coefficients [ICC] = 0.94), likelihood to cause harm (ICC = 0.89), and ability to simplify medication list (ICC = 0.90). Multivariate analyses demonstrated number of medicines (
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